Muriel Bowser Declares Victory
On June 22nd, 2022, Muriel Bowser won her second term for DC Mayor. Bowser’s message: she is the next Marion Barry, the only mayor to serve three consecutive terms. During her election night victory, she said: “Tonight we choose a future where we won’t lose our Chocolate City, but we will invest in it, and we will continue to be a city for Black Washingtonians.” from DCist
Mayor Bowser also won with just 49.8% of the vote. As someone who is interested in election data, I wanted to better understand the results of the elections through multiple visualizations.
Across the three visualizations, green will represent Mayor Bowser, blue will represent Robert White, and orange will represent Trayon White.
Here is data from the DC Elections office of the 2022 Primary. I did some simple filtering to narrow it to the Mayor’s election.
| precinct | ward | nvotes | bowser | twhite | rwhite |
|---|---|---|---|---|---|
| 1 | 6 | 1364 | 608 | 167 | 589 |
| 2 | 2 | 90 | 34 | 2 | 54 |
| 3 | 2 | 571 | 380 | 17 | 174 |
| 4 | 2 | 714 | 467 | 14 | 233 |
| 5 | 2 | 721 | 552 | 8 | 161 |
| 6 | 2 | 669 | 502 | 10 | 157 |
| 7 | 3 | 570 | 366 | 9 | 195 |
| 8 | 3 | 1312 | 967 | 13 | 332 |
| 9 | 3 | 503 | 414 | 3 | 86 |
| 10 | 3 | 816 | 620 | 8 | 188 |
| 11 | 3 | 1292 | 688 | 19 | 585 |
| 12 | 3 | 238 | 179 | 4 | 55 |
| 13 | 2 | 549 | 361 | 5 | 183 |
| 14 | 2 | 945 | 488 | 16 | 441 |
| 15 | 2 | 1185 | 579 | 17 | 589 |
| 16 | 2 | 1324 | 734 | 34 | 556 |
| 17 | 2 | 1397 | 663 | 43 | 691 |
| 18 | 6 | 0 | 0 | 0 | 0 |
| 19 | 5 | 1426 | 621 | 105 | 700 |
| 20 | 1 | 276 | 120 | 21 | 135 |
| 21 | 6 | 0 | 0 | 0 | 0 |
| 22 | 1 | 1594 | 788 | 40 | 766 |
| 23 | 1 | 1045 | 455 | 49 | 541 |
| 24 | 1 | 1144 | 541 | 9 | 594 |
| 25 | 1 | 1797 | 883 | 19 | 895 |
| 26 | 3 | 1456 | 820 | 13 | 623 |
| 27 | 3 | 1301 | 838 | 18 | 445 |
| 28 | 3 | 1186 | 813 | 16 | 357 |
| 29 | 3 | 596 | 382 | 12 | 202 |
| 30 | 3 | 759 | 514 | 7 | 238 |
| 31 | 3 | 1415 | 938 | 15 | 462 |
| 32 | 3 | 1506 | 979 | 19 | 508 |
| 33 | 3 | 1562 | 963 | 16 | 583 |
| 34 | 3 | 1992 | 1041 | 42 | 909 |
| 35 | 1 | 1457 | 606 | 30 | 821 |
| 36 | 1 | 1341 | 508 | 102 | 731 |
| 37 | 1 | 1054 | 448 | 55 | 551 |
| 38 | 1 | 974 | 352 | 54 | 568 |
| 39 | 1 | 1578 | 696 | 52 | 830 |
| 40 | 1 | 1500 | 661 | 44 | 795 |
| 41 | 1 | 1078 | 434 | 48 | 596 |
| 42 | 1 | 691 | 284 | 22 | 385 |
| 43 | 1 | 616 | 248 | 50 | 318 |
| 44 | 5 | 761 | 371 | 104 | 286 |
| 45 | 4 | 850 | 362 | 56 | 432 |
| 46 | 4 | 1107 | 467 | 65 | 575 |
| 47 | 4 | 1287 | 533 | 45 | 709 |
| 48 | 4 | 1114 | 561 | 50 | 503 |
| 49 | 4 | 327 | 115 | 25 | 187 |
| 50 | 3 | 1088 | 673 | 14 | 401 |
| 51 | 4 | 1766 | 1205 | 22 | 539 |
| 52 | 4 | 797 | 582 | 4 | 211 |
| 53 | 4 | 488 | 291 | 22 | 175 |
| 54 | 4 | 845 | 406 | 44 | 395 |
| 55 | 4 | 847 | 388 | 66 | 393 |
| 56 | 4 | 1088 | 480 | 87 | 521 |
| 57 | 4 | 824 | 352 | 55 | 417 |
| 58 | 4 | 745 | 340 | 59 | 346 |
| 59 | 4 | 999 | 471 | 60 | 468 |
| 60 | 4 | 593 | 328 | 50 | 215 |
| 61 | 4 | 612 | 350 | 39 | 223 |
| 62 | 4 | 1766 | 1151 | 30 | 585 |
| 63 | 4 | 1576 | 783 | 68 | 725 |
| 64 | 4 | 924 | 503 | 48 | 373 |
| 65 | 4 | 1051 | 564 | 86 | 401 |
| 66 | 5 | 1881 | 922 | 185 | 774 |
| 67 | 5 | 1215 | 635 | 84 | 496 |
| 68 | 5 | 837 | 383 | 59 | 395 |
| 69 | 5 | 926 | 450 | 63 | 413 |
| 70 | 5 | 608 | 290 | 44 | 274 |
| 71 | 5 | 890 | 467 | 87 | 336 |
| 72 | 5 | 1108 | 483 | 166 | 459 |
| 73 | 5 | 857 | 375 | 61 | 421 |
| 74 | 5 | 1508 | 640 | 152 | 716 |
| 75 | 5 | 1265 | 463 | 114 | 688 |
| 76 | 5 | 463 | 162 | 52 | 249 |
| 77 | 5 | 899 | 371 | 105 | 423 |
| 78 | 5 | 687 | 256 | 122 | 309 |
| 79 | 5 | 379 | 144 | 84 | 151 |
| 80 | 7 | 2334 | 976 | 324 | 1034 |
| 81 | 6 | 872 | 382 | 50 | 440 |
| 82 | 6 | 982 | 427 | 59 | 496 |
| 83 | 6 | 1227 | 510 | 61 | 656 |
| 84 | 6 | 838 | 455 | 17 | 366 |
| 85 | 6 | 1127 | 622 | 20 | 485 |
| 86 | 6 | 631 | 323 | 9 | 299 |
| 87 | 6 | 129 | 69 | 9 | 51 |
| 88 | 6 | 965 | 507 | 19 | 439 |
| 89 | 6 | 1212 | 677 | 14 | 521 |
| 90 | 6 | 606 | 349 | 11 | 246 |
| 91 | 6 | 1478 | 669 | 98 | 711 |
| 92 | 7 | 293 | 107 | 94 | 92 |
| 93 | 7 | 398 | 191 | 93 | 114 |
| 94 | 7 | 507 | 213 | 115 | 179 |
| 95 | 7 | 340 | 135 | 79 | 126 |
| 96 | 7 | 491 | 203 | 132 | 156 |
| 97 | 7 | 311 | 146 | 83 | 82 |
| 98 | 7 | 499 | 244 | 122 | 133 |
| 99 | 7 | 344 | 166 | 74 | 104 |
| 100 | 7 | 519 | 204 | 180 | 135 |
| 101 | 7 | 481 | 221 | 84 | 176 |
| 102 | 7 | 564 | 245 | 161 | 158 |
| 103 | 7 | 799 | 327 | 240 | 232 |
| 104 | 7 | 741 | 285 | 230 | 226 |
| 105 | 7 | 572 | 253 | 145 | 174 |
| 106 | 7 | 775 | 377 | 175 | 223 |
| 107 | 7 | 295 | 133 | 104 | 58 |
| 108 | 7 | 408 | 215 | 44 | 149 |
| 109 | 7 | 419 | 220 | 24 | 175 |
| 110 | 7 | 1232 | 603 | 198 | 431 |
| 111 | 7 | 549 | 270 | 123 | 156 |
| 112 | 8 | 482 | 227 | 107 | 148 |
| 113 | 7 | 791 | 397 | 130 | 264 |
| 114 | 8 | 619 | 237 | 186 | 196 |
| 115 | 8 | 441 | 159 | 197 | 85 |
| 116 | 8 | 654 | 243 | 267 | 144 |
| 117 | 8 | 432 | 145 | 194 | 93 |
| 118 | 8 | 554 | 174 | 250 | 130 |
| 119 | 8 | 417 | 131 | 171 | 115 |
| 120 | 8 | 509 | 179 | 203 | 127 |
| 121 | 8 | 732 | 284 | 283 | 165 |
| 122 | 8 | 389 | 180 | 127 | 82 |
| 123 | 8 | 486 | 219 | 153 | 114 |
| 124 | 8 | 627 | 268 | 208 | 151 |
| 125 | 8 | 795 | 309 | 315 | 171 |
| 126 | 8 | 694 | 263 | 281 | 150 |
| 127 | 6 | 1534 | 778 | 128 | 628 |
| 128 | 6 | 707 | 325 | 51 | 331 |
| 129 | 2 | 2529 | 1300 | 148 | 1081 |
| 130 | 6 | 340 | 189 | 5 | 146 |
| 131 | 6 | 668 | 291 | 30 | 347 |
| 132 | 7 | 408 | 194 | 94 | 120 |
| 133 | 8 | 330 | 175 | 62 | 93 |
| 134 | 8 | 479 | 172 | 202 | 105 |
| 135 | 5 | 994 | 462 | 69 | 463 |
| 136 | 3 | 380 | 189 | 2 | 189 |
| 137 | 1 | 424 | 202 | 12 | 210 |
| 138 | 3 | 1075 | 665 | 19 | 391 |
| 139 | 5 | 1039 | 604 | 107 | 328 |
| 140 | 8 | 1279 | 588 | 166 | 525 |
| 141 | 2 | 892 | 429 | 13 | 450 |
| 142 | 6 | 798 | 413 | 51 | 334 |
| 143 | 2 | 226 | 130 | 3 | 93 |
| 144 | 6 | 897 | 294 | 44 | 559 |
So what does this mean? It’s hard to make heads or tails of a bunch of numbers. Luckily, R allows us to visualize the data in multiple ways to tell different stories.
Let’s look at total number of votes per precinct in a simple linegraph.

This would give us the impression that Mayor Bowser is the clear and consistent favorite. What if we looked at the percent point break down per precinct?

It looks a little closer. Mayor Bowser and Robert White are neck and neck in a few precincts. Trayon White is the clear favorite in a few. The two gaps are the precincts that don’t report any votes.
Lines on a graph are great, but they don’t explain very well where these close precincts were in the city. In which precincts did each candidate perform well?
This is a map of dc precincts courtesy of the DC Department of Elections.
As we can see, there tends to be a geographic cluster where each candidate performed well. Unfortunately, these choropleths only explain where each candidate did well relative to their best performance. Trayon White’s best performance was with 40% of the vote, whereas Mayor Bowser won some with a blowout of close to 80%.
One final item to consider is turnout, which measures the share of registered voters per precinct who turned out to vote. As we can see in the graph below, turnout of each candidate’s voter base varied, but Bowser consistently had the highest percent of the vote per precinct, which is likely what brought her to victory.

I hope to visualize the data from the next election cycle and compare it to these results to continue to look for trends within elections.